4,461 research outputs found

    Exploring the relationship between spatial cognitive ability and movement ecology

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    Spatial cognitive ability is hypothesised to be a key determinant of animal movement patterns. However, empirical demonstrations linking intra-individual variations in spatial cognitive ability with movement ecology are rare. I reared ~200 simultaneously hatched pheasant chicks per year over three years in standardised conditions without parents, controlling for the confounding effects of experience, maternal influences and age. I tested the chicks on spatial cognitive tasks from three weeks old to obtain measures of inherent, early-life spatial cognitive ability. Each year, I released birds when 10 weeks old into an open-topped enclosure in woodland. Birds dispersed from this enclosure after about one-month. Importantly, all birds were released into the same, novel area simultaneously, thus their experiences and opportunities were standardised. I remotely tracked pheasant movement through either RFID antenna placed under 43 supplementary feeders situated throughout our field site (2016) or by using a novel reverse-GPS tracking system (2017-2018). Spatial cognitive ability, determined through binary spatial discrimination (2016) or a Barnes maze (2017), was related to the diversity of foraging sites an individual used (Chapter 2: 2016). Those with better spatial cognitive ability used a more diverse range of artificial feeders than poor performing counterparts, perhaps to retain a buffer of alternative foraging sites where resource profitability was known. I found no relationship between the timing of daily foraging onset between birds of differing cognitive ability (Chapter 3; 2016), which I had hypothesised to be a consequence of birds developing efficient routes between refuges and feeders. After establishing a reverse GPS system on our field site (Chapter 4: 2017), I collected more detailed information about pheasant movement and found that birds with higher accuracy scores on the cognition tasks initially moved between foraging and resting sites more slowly than inaccurate birds in novel environments, perhaps to gather more detailed information. Accurate birds increased their speed over one month to match the same speed as inaccurate birds. All birds increased the straightness of their routes at a similar rate. Lastly, I found intraspecific differences in the orientation strategy that birds used to solve a dual strategy maze task (Chapter 5: 2018). These differences predicted habitat use after release: birds that utilised landmarks (allocentric strategies) showed less aversion to urban habitats (farm buildings/yards) than egocentric/mixed strategy birds, which is potentially due to the presence of large, stable landmarks within these habitats. In this thesis, I provide several empirical links between spatial cognitive ability and movement ecology across a range of ecological contexts. I suggest that very specific cognitive processes may govern particular movement behaviours and that there is not one overarching general spatial ability.European Commissio

    A guide to pre-processing high-throughput animal tracking data

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    1. Modern, high-throughput animal tracking studies collect increasingly large volumes of data at very fine temporal scales. At these scales, location error can exceed the animal’s step size, leading to mis-estimation of key movement metrics such as speed. ‘Cleaning’ the data to reduce location errors prior to analyses is one of the main ways movement ecologists deal with noisy data, and has the advantage of being more scalable to massive datasets than more complex methods. Though data cleaning is widely recommended, and ecologists routinely consider cleaned data to be the ground-truth, inclusive uniform guidance on this crucial step, and on how to organise the cleaning of massive datasets, is still rather scarce. 2. A pipeline for cleaning massive high-throughput datasets must balance ease of use and computationally efficient signal vs. noise screening, in which location errors are rejected without discarding valid animal movements. Another useful feature of a pre-processing pipeline is efficiently segmenting and clustering location data for statistical methods, while also being scalable to large datasets and robust to imperfect sampling. Manual methods being prohibitively time consuming, and to boost reproducibility, a robust pre-processing pipeline must be automated. 3. In this article we provide guidance on building pipelines for pre-processing high-throughput animal tracking data in order to prepare it for subsequent analysis. Our recommended pipeline, consisting of removing outliers, smoothing the filtered result, and thinning it to a uniform sampling interval, is applicable to many massive tracking datasets. We apply this pipeline to simulated movement data with location errors, and also show a case study of how large volumes of cleaned data can be transformed into biologically meaningful ‘residence patches’, for quick biological inference on animal space use. We use calibration data to illustrate how pre-processing improves its quality, and to verify that the residence patch synthesis accurately captures animal space use. Finally, turning to tracking data from Egyptian fruit bats (Rousettus aegyptiacus), we demonstrate the pre-processing pipeline and residence patch method in a fully worked out example. 4. To help with fast implementation of standardised methods, we developed the R package atlastools, which we also introduce here. Our pre-processing pipeline and atlastools can be used with any high-throughput animal movement data in which the high data-volume combined with knowledge of the tracked individuals’ movement capacity can be used to reduce location errors. The atlastools function is easy to use for beginners, while providing a template for further development. The use of common pre-processing steps that are simple yet robust promotes standardised methods in the field of movement ecology and leads to better inferences from data

    Passive acoustic methods for tracking the 3D movements of small cetaceans around marine structures

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    This research was funded through a research grant from the Scottish Government as part of the Marine Mammal Scientific Support Program MMSS/002/15.A wide range of anthropogenic structures exist in the marine environment with the extent of these set to increase as the global offshore renewable energy industry grows. Many of these pose acute risks to marine wildlife; for example, tidal energy generators have the potential to injure or kill seals and small cetaceans through collisions with moving turbine parts. Information on fine scale behaviour of animals close to operational turbines is required to understand the likely impact of these new technologies. There are inherent challenges associated with measuring the underwater movements of marine animals which have, so far, limited data collection. Here, we describe the development and application of a system for monitoring the three-dimensional movements of cetaceans in the immediate vicinity of a subsea structure. The system comprises twelve hydrophones and software for the detection and localisation of vocal marine mammals. We present data demonstrating the systems practical performance during a deployment on an operational tidal turbine between October 2017 and October 2019. Three-dimensional locations of cetaceans were derived from the passive acoustic data using time of arrival differences on each hydrophone. Localisation accuracy was assessed with an artificial sound source at known locations and a refined method of error estimation is presented. Calibration trials show that the system can accurately localise sounds to 2m accuracy within 20m of the turbine but that localisations become highly inaccurate at distances greater than 35m. The system is currently being used to provide data on rates of encounters between cetaceans and the turbine and to provide high resolution tracking data for animals close to the turbine. These data can be used to inform stakeholders and regulators on the likely impact of tidal turbines on cetaceans.Publisher PDFPeer reviewe

    Sound Event Localization, Detection, and Tracking by Deep Neural Networks

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    In this thesis, we present novel sound representations and classification methods for the task of sound event localization, detection, and tracking (SELDT). The human auditory system has evolved to localize multiple sound events, recognize and further track their motion individually in an acoustic environment. This ability of humans makes them context-aware and enables them to interact with their surroundings naturally. Developing similar methods for machines will provide an automatic description of social and human activities around them and enable machines to be context-aware similar to humans. Such methods can be employed to assist the hearing impaired to visualize sounds, for robot navigation, and to monitor biodiversity, the home, and cities. A real-life acoustic scene is complex in nature, with multiple sound events that are temporally and spatially overlapping, including stationary and moving events with varying angular velocities. Additionally, each individual sound event class, for example, a car horn can have a lot of variabilities, i.e., different cars have different horns, and within the same model of the car, the duration and the temporal structure of the horn sound is driver dependent. Performing SELDT in such overlapping and dynamic sound scenes while being robust is challenging for machines. Hence we propose to investigate the SELDT task in this thesis and use a data-driven approach using deep neural networks (DNNs). The sound event detection (SED) task requires the detection of onset and offset time for individual sound events and their corresponding labels. In this regard, we propose to use spatial and perceptual features extracted from multichannel audio for SED using two different DNNs, recurrent neural networks (RNNs) and convolutional recurrent neural networks (CRNNs). We show that using multichannel audio features improves the SED performance for overlapping sound events in comparison to traditional single-channel audio features. The proposed novel features and methods produced state-of-the-art performance for the real-life SED task and won the IEEE AASP DCASE challenge consecutively in 2016 and 2017. Sound event localization is the task of spatially locating the position of individual sound events. Traditionally, this has been approached using parametric methods. In this thesis, we propose a CRNN for detecting the azimuth and elevation angles of multiple temporally overlapping sound events. This is the first DNN-based method performing localization in complete azimuth and elevation space. In comparison to parametric methods which require the information of the number of active sources, the proposed method learns this information directly from the input data and estimates their respective spatial locations. Further, the proposed CRNN is shown to be more robust than parametric methods in reverberant scenarios. Finally, the detection and localization tasks are performed jointly using a CRNN. This method additionally tracks the spatial location with time, thus producing the SELDT results. This is the first DNN-based SELDT method and is shown to perform equally with stand-alone baselines for SED, localization, and tracking. The proposed SELDT method is evaluated on nine datasets that represent anechoic and reverberant sound scenes, stationary and moving sources with varying velocities, a different number of overlapping sound events and different microphone array formats. The results show that the SELDT method can track multiple overlapping sound events that are both spatially stationary and moving

    Abstracts on Radio Direction Finding (1899 - 1995)

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    The files on this record represent the various databases that originally composed the CD-ROM issue of "Abstracts on Radio Direction Finding" database, which is now part of the Dudley Knox Library's Abstracts and Selected Full Text Documents on Radio Direction Finding (1899 - 1995) Collection. (See Calhoun record https://calhoun.nps.edu/handle/10945/57364 for further information on this collection and the bibliography). Due to issues of technological obsolescence preventing current and future audiences from accessing the bibliography, DKL exported and converted into the three files on this record the various databases contained in the CD-ROM. The contents of these files are: 1) RDFA_CompleteBibliography_xls.zip [RDFA_CompleteBibliography.xls: Metadata for the complete bibliography, in Excel 97-2003 Workbook format; RDFA_Glossary.xls: Glossary of terms, in Excel 97-2003 Workbookformat; RDFA_Biographies.xls: Biographies of leading figures, in Excel 97-2003 Workbook format]; 2) RDFA_CompleteBibliography_csv.zip [RDFA_CompleteBibliography.TXT: Metadata for the complete bibliography, in CSV format; RDFA_Glossary.TXT: Glossary of terms, in CSV format; RDFA_Biographies.TXT: Biographies of leading figures, in CSV format]; 3) RDFA_CompleteBibliography.pdf: A human readable display of the bibliographic data, as a means of double-checking any possible deviations due to conversion

    Magnetic Resonance Q Mapping Reveals a Decrease in Microvessel Density in the arcAβ Mouse Model of Cerebral Amyloidosis

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    Alterations in density and morphology of the cerebral microvasculature have been reported to occur in Alzheimer's disease patients and animal models of the disease. In this study we compared magnetic resonance imaging (MRI) techniques for their utility to detect age-dependent changes of the cerebral vasculature in the arcAβ mouse model of cerebral amyloidosis. Dynamic susceptibility contrast (DSC)-MRI was performed by tracking the passage of a superparamagnetic iron oxide nanoparticle in the brain with dynamic gradient echo planar imaging (EPI). From this measurements relative cerebral blood volume [rCBV(DSC)] and relative cerebral blood flow (rCBF) were estimated. For the same animal maps of the relaxation shift index Q were computed from high resolution gradient echo and spin echo data that were acquired before and after superparamagnetic iron oxide (SPIO) nanoparticle injection. Q-values were used to derive estimates of microvessel density. The change in the relaxation rates ΔR∗2 obtained from pre- and post-contrast gradient echo data was used for the alternative determination of rCBV [rCBV(ΔR∗2)]. Linear mixed effects modeling found no significant association between rCBV(DSC), rCBV(ΔR∗2), rCBF, and Q with genotype in 13-month old mice [compared to age- matched non-transgenic littermates (NTLs)] for any of the evaluated brain regions. In 24-month old mice there was a significant association for rCBV(DSC) with genotype in the cerebral cortex, and for rCBV(ΔR∗2) in the cerebral cortex and cerebellum. For rCBF there was a significant association in the cerebellum but not in other brain regions. Q-values in the olfactory bulb, cerebral cortex, striatum, hippocampus, and cerebellum in 24-month old mice were significantly associated with genotype. In those regions Q-values were reduced between 11 and 26% in arcAβ mice compared to age-matched NTLs. Vessel staining with CD31 immunohistochemistry confirmed a reduction of microvessel density in the old arcAβ mice. We further demonstrated a region- specific association between parenchymal and vascular deposition of β-amyloid and decreased vascular density, without a correlation with the amount of Aβ deposition. We found that Q mapping was more suitable than the hemodynamic read-outs to detect amyloid-related degeneration of the cerebral microvasculature

    Mapping Myocardial Elasticity with Intracardiac Acoustic Radiation Force Impulse Methods

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    <p>Implemented on an intracardiac echocardiography transducer, acoustic radiation force methods may provide a useful means of characterizing the heart's elastic properties. Elasticity imaging may be of benefit for diagnosis and characterization of infarction and heart failure, as well as for guidance of ablation therapy for the treatment of arrhythmias. This thesis tests the hypothesis that with appropriately designed imaging sequences, intracardiac acoustic radiation force impulse (ARFI) imaging and shear wave elasticity imaging (SWEI) are viable tools for quantification of myocardial elasticity, both temporally and spatially. Multiple track location SWEI (MTL-SWEI) is used to show that, in healthy in vivo porcine ventricles, shear wave speeds follow the elasticity changes with contraction and relaxation of the myocardium, varying between 0.9 and 2.2 m/s in diastole and 2.6 and 5.1 m/s in systole. Infarcted tissue is less contractile following infarction, though not unilaterally stiffer. Single-track-location SWEI (STL-SWEI) is proven to provide suppression of speckle noise and enable improved resolution of structures smaller than 2 mm in diameter compared to ARFI and MTL-SWEI. Contrast to noise ratio and lateral edge resolution are shown to vary with selection of time step for ARFI and arrival time regression filter size for STL-SWEI and MTL-SWEI. </p><p>In 1.5 mm targets, STL-SWEI achieves alternately the tightest resolution (0.3 mm at CNR = 3.5 for a 0.17 mm filter) and highest CNR (8.5 with edge width = 0.7 mm for a 0.66 mm filter) of the modalities, followed by ARFI and then MTL-SWEI.</p><p>In larger, 6 mm targets, the CNR-resolution tradeoff curves for ARFI and STL-SWEI overlap for ARFI time steps up to 0.5 ms and kernels ≤\leq1 mm for STL-SWEI. STL-SWEI can operate either with a 25 dB improvement over MTL-SWEI in CNR at the same resolution, or with edge widths 5×\times as narrow at equivalent CNR values, depending on the selection of regression filter size. Ex vivo ablations are used to demonstrate that ARFI, STL-SWEI and MTL-SWEI each resolve ablation lesions between 0.5 and 1 cm in diameter and gaps between lesions smaller than 5 mm in 3-D scans. Differences in contrast, noise, and resolution between the modalities are discussed. All three modalities are also shown to resolve ``x''-shaped ablations up to 22 mm in depth with good visual fidelity and correspondence to surface photographs, with STL-SWEI providing the highest quality images. Series of each type of image, registered using 3-D data from an electroanatomical mapping system, are used to build volumes that show ablations in in vivo canine atria. In vivo images are shown to be subject to increased noise due to tissue and transducer motion, and the challenges facing the proposed system are discussed. Ultimately, intracardiac acoustic radiation force methods are demonstrated to be promising tools for characterizing dynamic myocardial elasticity and imaging radiofrequency ablation lesions.</p>Dissertatio

    ConservationBots: Autonomous Aerial Robot for Fast Robust Wildlife Tracking in Complex Terrains

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    Today, the most widespread, widely applicable technology for gathering data relies on experienced scientists armed with handheld radio telemetry equipment to locate low-power radio transmitters attached to wildlife from the ground. Although aerial robots can transform labor-intensive conservation tasks, the realization of autonomous systems for tackling task complexities under real-world conditions remains a challenge. We developed ConservationBots-small aerial robots for tracking multiple, dynamic, radio-tagged wildlife. The aerial robot achieves robust localization performance and fast task completion times -- significant for energy-limited aerial systems while avoiding close encounters with potential, counter-productive disturbances to wildlife. Our approach overcomes the technical and practical problems posed by combining a lightweight sensor with new concepts: i) planning to determine both trajectory and measurement actions guided by an information-theoretic objective, which allows the robot to strategically select near-instantaneous range-only measurements to achieve faster localization, and time-consuming sensor rotation actions to acquire bearing measurements and achieve robust tracking performance; ii) a bearing detector more robust to noise and iii) a tracking algorithm formulation robust to missed and false detections experienced in real-world conditions. We conducted extensive studies: simulations built upon complex signal propagation over high-resolution elevation data on diverse geographical terrains; field testing; studies with wombats (Lasiorhinus latifrons; nocturnal, vulnerable species dwelling in underground warrens) and tracking comparisons with a highly experienced biologist to validate the effectiveness of our aerial robot and demonstrate the significant advantages over the manual method.Comment: 33 pages, 21 figure
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